The benefit of advance load information for truckload carriers

Anticipatory freight selection in intermodal long-haul round-trips

“…One of these insights concerns the value of dynamic, in-advance, information itself. Knowledge of load information, one or two days in advance, has been shown to improve performance in trucking companies [Zolfagharinia and Haughton, 2014]. Another of these insights concerns stochastic freight (load) demand, where demand reveals dynamically with time or with events.…”

Multi-period stochastic optimization problems in transportation management

“…Several authors have observed that this version of the problem can be formulated as a min-cost network flow problem and hence, can be solved in polynomial time; see section 7.4 hereunder. [Tjokroamidjojo et al, 2006] and [Zolfagharinia & Haughton, 2014] have used and solved this formulation in a deterministic rolling-horizon framework which follows the generic description provided in [Sethi & Sorger, 1991]. Their main objective was to examine the influence of the length of the rolling horizon, the load density, the trip length and the fleet size on the quality of the solutions obtained.…”

Value of information in agro-food logistics management : a case of the Dutch floriculture supply chain network

“…In terms of information sources, chain-internal information sharing has been the focal point of the literature (covering about 69% of the reviewed articles). Information can be shared from downstream to upstream in the chain, such as demand information (Viswanathan et al, 2007), or reversely, such as manufacturer's production capacity information shared to retailers (Bakal et al, 2011), or between actors of two different chains at the same stage such as sharing load information among shippers (Zolfagharinia & Haughton, 2014). In chain-internal information sharing, sharing raw data (e.g.…”

“…Timeliness (Liu et al, 2009) Product location (tracking) q-period lagged information (q = 0, 1, 2, …; q = 0: real-time information) (Tjokroamidjojo et al, 2006) Advance load information Number of days in advance that the information is shared (Zolfagharinia & Haughton, 2014) (Banerjee & Golhar, 2017) Product specifications Two moments of sharing the information by the retailer: before or after the supplier starts the base unit production Accuracy (Ketzenberg, 2009) Demand, yield, capacity A probability p (0, 0.05, 0.25, 0.5) that inaccuracy occurs in randomizing the information (p = 0: accurate information) (Flamini et al, 2011) Product location Randomizing measurement errors (follow a uniform distribution) (Kaman et al, 2013) Shopfloor operations Randomizing errors between actual and observed states (follow a uniform distribution) (Cannella et al, 2015) Inventory level Adding error as a percentage of the record (Cui et al, 2015) POS, replenishment policy Adding decision deviations (follow a normal distribution) to the order quantity, which is based on the replenishment policy (Kwak & Gavirneni, 2015) Demand Adding information errors (follow a normal distribution) to the actual values (Ketzenberg et al, 2015) Product condition (Rached et al, 2015) Demand, delivery lead time (Lu et al, 2017) Demand…”

“…x (Hussain & Drake, 2011) Demand Order batch size x (Flapper et al, 2012) Advance return Return time x (Bendre & Nielsen, 2013) Lead time Lost-sale cost x (Kaman et al, 2013) Shopfloor operations Holding cost x (Ketzenberg et al, 2013) Unattended POS (vending machine) Demand uncertainty x (Ganesh et al, 2014b) Demand Product substitution x (Ruiz-Benítez et al, 2014) Return-product quantity Shipping cost x Decay rate of product x (Zolfagharinia & Haughton, 2014) Advance load Service radius and trip length x (Ketzenberg et al, 2015) Product condition Demand uncertainty x (Rached et al, 2015) Demand and delivery lead time Holding cost x (Yan & Pei, 2015) Demand Product differentiation x (Shang et al, 2010) Demand Logistics system VOI is significant when the logistics systems is flexible to enable flexible ordering (Xue et al, 2011) Supply quantity Review policy VOI depends on the inventory review policy (Cho & Lee, 2013) Demand Lead time VOI is significant when lead time is shorter than the seasonal period (Babai et al, 2016) Demand Autoregressive demand parameter VOI is significant when the parameter is less than 0.7 Table 2.4. Employed decision support models in the reviewed articles…”